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🉐#AI finds where IG photos are taken🉐
👉Brilliant work of Depoorter, Belgium artist that handles #privacy, #AI & #socialmedia
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Recorded open cameras for weeks
✅Scraped all #Instagram photos
✅Matching Instagram vs. footage
More: https://bit.ly/3eL5dfc
👉Brilliant work of Depoorter, Belgium artist that handles #privacy, #AI & #socialmedia
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Recorded open cameras for weeks
✅Scraped all #Instagram photos
✅Matching Instagram vs. footage
More: https://bit.ly/3eL5dfc
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🈯SAMURAI: in-the-wild Shape/Material🈯
👉#Google SAMURAI: shape, BRDF, per-image pose & illumination. Relightable #3D assets for #AR/#VR.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Parametrization for varying distances
✅Camera multiplex optimization
✅Posterior scaling of input images
✅Explicit meshes extraction with BRDF
✅Code/data soon available ->#NeurIPS
More: https://bit.ly/3BKWgf3
👉#Google SAMURAI: shape, BRDF, per-image pose & illumination. Relightable #3D assets for #AR/#VR.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Parametrization for varying distances
✅Camera multiplex optimization
✅Posterior scaling of input images
✅Explicit meshes extraction with BRDF
✅Code/data soon available ->#NeurIPS
More: https://bit.ly/3BKWgf3
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🟨 Lang<->Pics in 100+ Languages 🟨
👉#Google PaLI: unified lang-image #AI to perform tasks in 109 languages 🤯
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅PaLI: Pathways Lang & Image model
✅Answering, captioning, reasoning, etc
✅From Eng. to 109 lang. understanding
✅The new SOTA on several datasets
More: https://bit.ly/3QMslHC
👉#Google PaLI: unified lang-image #AI to perform tasks in 109 languages 🤯
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅PaLI: Pathways Lang & Image model
✅Answering, captioning, reasoning, etc
✅From Eng. to 109 lang. understanding
✅The new SOTA on several datasets
More: https://bit.ly/3QMslHC
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🍐PeRFception: Largest IR Dataset🍐
👉#Nvidia, a new frontier in data collection via Plenoxels: same info, -96.4% in size.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅POSTECH + NVIDIA + Caltech = 🤯
✅Size: -96.4% from original dataset!
✅2D/3D image/object class/semantic
✅Ready-to-use pipeline for implicit dataset
More: https://bit.ly/3eW9hJA
👉#Nvidia, a new frontier in data collection via Plenoxels: same info, -96.4% in size.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅POSTECH + NVIDIA + Caltech = 🤯
✅Size: -96.4% from original dataset!
✅2D/3D image/object class/semantic
✅Ready-to-use pipeline for implicit dataset
More: https://bit.ly/3eW9hJA
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🐸 CHARL-E: Stable Diffusion in 1 click 🐸
👉CHARL-E packages Stable Diffusion into a simple app.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅No setup, dependencies, or internet
✅Images with 1-click on #macbook
✅Suitable only for M1/M2 processor
✅Source code under MIT license
More: https://bit.ly/3xv2z3G
👉CHARL-E packages Stable Diffusion into a simple app.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅No setup, dependencies, or internet
✅Images with 1-click on #macbook
✅Suitable only for M1/M2 processor
✅Source code under MIT license
More: https://bit.ly/3xv2z3G
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🍋YOLOPv2: Better Driving Perception🍋
👉YOLOPv2: simultaneous object, road segmentation & lane detection
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅E2E perception net with better backbone
✅Efficient ELAN for reasonable memory
✅Stability for adapting to scenarios
✅SOTA on BDD100K, +50% faster!
✅Source code under MIT license
More: https://bit.ly/3LvYGBh
👉YOLOPv2: simultaneous object, road segmentation & lane detection
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅E2E perception net with better backbone
✅Efficient ELAN for reasonable memory
✅Stability for adapting to scenarios
✅SOTA on BDD100K, +50% faster!
✅Source code under MIT license
More: https://bit.ly/3LvYGBh
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🍈SegNeXt: new SOTA in Semantic Seg.🍈
👉SOTA (by large margin) on ADE20K, Cityscapes, COCO-Stuff, Pascal VOC, Pascal Context, and iSAID 🤯
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Novel tailored network architecture
✅Spatial attention via multi-scale feats
✅Encoder + conv. better than transformers
✅SOTA on several datasets (ADE20K, etc.)
More: https://bit.ly/3UrZhrH
👉SOTA (by large margin) on ADE20K, Cityscapes, COCO-Stuff, Pascal VOC, Pascal Context, and iSAID 🤯
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Novel tailored network architecture
✅Spatial attention via multi-scale feats
✅Encoder + conv. better than transformers
✅SOTA on several datasets (ADE20K, etc.)
More: https://bit.ly/3UrZhrH
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🦪StereoVoxelNet: RT Obstacles Detection🦪
👉Novel deep neural approach to detect occupancy from stereo images directly
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Occupancy voxels via deep learning
✅RT on Jetson-TX2 (-98% CPU of SOTA)
✅Optimization via octrees / sparse conv.
✅Real-world stereo in/outdoor dataset
More: https://bit.ly/3BylAn3
👉Novel deep neural approach to detect occupancy from stereo images directly
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Occupancy voxels via deep learning
✅RT on Jetson-TX2 (-98% CPU of SOTA)
✅Optimization via octrees / sparse conv.
✅Real-world stereo in/outdoor dataset
More: https://bit.ly/3BylAn3
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🚜 NeRF-Factory: a NeRF collection 🚜
👉PyTorch-reimplemented NeRF library with 7 popular models/implementations & 7 datasets
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅NeRF: Project | Paper | Code
✅NeRF++: Paper | Code
✅DVGO: Project | Paper v1/v2 | Code
✅Plenoxels: Project | Paper | Code
✅Mip-NeRF: Project | Paper | Code
✅Mip-NeRF360: Project | Paper | Code
✅Ref-NeRF: Project | Paper | Code
More: https://bit.ly/3qUgmgC
👉PyTorch-reimplemented NeRF library with 7 popular models/implementations & 7 datasets
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅NeRF: Project | Paper | Code
✅NeRF++: Paper | Code
✅DVGO: Project | Paper v1/v2 | Code
✅Plenoxels: Project | Paper | Code
✅Mip-NeRF: Project | Paper | Code
✅Mip-NeRF360: Project | Paper | Code
✅Ref-NeRF: Project | Paper | Code
More: https://bit.ly/3qUgmgC
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🥶 Lumos by #Nvidia: Relighting Portrait 🥶
👉The new SOTA in relighting without requiring a light stage
😎Review https://bit.ly/3dCH9ej
😎Project deepimagination.cc/Lumos
😎Paper arxiv.org/pdf/2209.10510.pdf
😎Demo http://imaginaire.cc/Lumos/
👉The new SOTA in relighting without requiring a light stage
😎Review https://bit.ly/3dCH9ej
😎Project deepimagination.cc/Lumos
😎Paper arxiv.org/pdf/2209.10510.pdf
😎Demo http://imaginaire.cc/Lumos/
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🍜 SURF-GAN: NeRF - >StyleGAN 🍜
👉 Editable portraits by injecting the NeRF's prior into StyleGAN
😎Review https://bit.ly/3SohEw3
😎Project jgkwak95.github.io/surfgan
😎Paper arxiv.org/pdf/2207.10257.pdf
😎Code github.com/jgkwak95/SURF-GAN
👉 Editable portraits by injecting the NeRF's prior into StyleGAN
😎Review https://bit.ly/3SohEw3
😎Project jgkwak95.github.io/surfgan
😎Paper arxiv.org/pdf/2207.10257.pdf
😎Code github.com/jgkwak95/SURF-GAN
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🔥#Google just announced "TensorStore"🔥
👉Novel open-source C++ / #Python library for storage/manipulation of high-dim data
😎Review https://bit.ly/3DLwbha
😎Project https://bit.ly/3C4T2TR
😎Code github.com/google/tensorstore
👉Novel open-source C++ / #Python library for storage/manipulation of high-dim data
😎Review https://bit.ly/3DLwbha
😎Project https://bit.ly/3C4T2TR
😎Code github.com/google/tensorstore
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🦠 Motion Transformer for #selfdriving 🦠
👉The 1st place solution for 2022 #waymo "motion prediction" challenge
😎Review https://bit.ly/3f8G4LD
😎Paper arxiv.org/pdf/2209.10033.pdf
😎Code github.com/sshaoshuai/MTR
👉The 1st place solution for 2022 #waymo "motion prediction" challenge
😎Review https://bit.ly/3f8G4LD
😎Paper arxiv.org/pdf/2209.10033.pdf
😎Code github.com/sshaoshuai/MTR
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💹 Image Synthesis @160+ FPS! 💹
👉Super-fast, 3D-Aware Image Synthesis with Sparse Voxels -> up to 167 FPS!
😎Review https://bit.ly/3r3ZNij
😎Paper arxiv.org/pdf/2206.07695.pdf
😎Project katjaschwarz.github.io/voxgraf
👉Super-fast, 3D-Aware Image Synthesis with Sparse Voxels -> up to 167 FPS!
😎Review https://bit.ly/3r3ZNij
😎Paper arxiv.org/pdf/2206.07695.pdf
😎Project katjaschwarz.github.io/voxgraf
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👛 #Nvidia GET3D: #3D generative #AI 👛
👉AI-based Textured 3D meshes with complex topology, rich geometry & hi-fi textures
😎Review https://bit.ly/3SgnT5h
😎Code github.com/nv-tlabs/GET3D
😎Project nv-tlabs.github.io/GET3D/
😎Paper nv-tlabs.github.io/GET3D/assets/paper.pdf
👉AI-based Textured 3D meshes with complex topology, rich geometry & hi-fi textures
😎Review https://bit.ly/3SgnT5h
😎Code github.com/nv-tlabs/GET3D
😎Project nv-tlabs.github.io/GET3D/
😎Paper nv-tlabs.github.io/GET3D/assets/paper.pdf
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🔥🔥 IDE-3D: source code is out! 🔥🔥
👉Novel, photorealistic, 3D-aware facial generator: source code just released!
😎Review https://bit.ly/3BNrO2C
😎Project mrtornado24.github.io/IDE-3D/
😎Code github.com/MrTornado24/IDE-3D
😎Paper arxiv.org/pdf/2205.15517.pdf
👉Novel, photorealistic, 3D-aware facial generator: source code just released!
😎Review https://bit.ly/3BNrO2C
😎Project mrtornado24.github.io/IDE-3D/
😎Code github.com/MrTornado24/IDE-3D
😎Paper arxiv.org/pdf/2205.15517.pdf
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🔥Diffusion Model of Neural Checkpoints🔥
👉Conditional diffusion model on Millions of checkpoints of a given task/architecture 🤯
😎Review https://bit.ly/3SBR4Qb
😎Project www.wpeebles.com/Gpt
😎Code github.com/wpeebles/G.pt
😎Paper arxiv.org/pdf/2209.12892.pdf
👉Conditional diffusion model on Millions of checkpoints of a given task/architecture 🤯
😎Review https://bit.ly/3SBR4Qb
😎Project www.wpeebles.com/Gpt
😎Code github.com/wpeebles/G.pt
😎Paper arxiv.org/pdf/2209.12892.pdf
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🔥 Semantic VISOR dataset is out! 🔥
👉Segmenting hands / active objects in egocentric video (millions masks)
😎Review https://bit.ly/3LOBLBv
😎Project epic-kitchens.github.io/VISOR/
😎Paper arxiv.org/pdf/2209.13064.pdf
👉Segmenting hands / active objects in egocentric video (millions masks)
😎Review https://bit.ly/3LOBLBv
😎Project epic-kitchens.github.io/VISOR/
😎Paper arxiv.org/pdf/2209.13064.pdf
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🥇🥇 Olympic Games in 2028? 🥇🥇
👉 In a few years, the fastest runner on earth will not be a human 🥶
😎Review https://bit.ly/3Rme3O3
👉 In a few years, the fastest runner on earth will not be a human 🥶
😎Review https://bit.ly/3Rme3O3
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🔥 SOTA ALERT: new Text-to-Video #AI 🔥
👉#META unveils a novel Text-to-Video (T2V) generation #AI
😎Review https://bit.ly/3E1ZDzG
😎Project https://makeavideo.studio/
😎Paper makeavideo.studio/Make-A-Video.pdf
👉#META unveils a novel Text-to-Video (T2V) generation #AI
😎Review https://bit.ly/3E1ZDzG
😎Project https://makeavideo.studio/
😎Paper makeavideo.studio/Make-A-Video.pdf
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